Uncertainty in Artificial Intelligence
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Combination of Upper and Lower Probabilities
Jose Cano, Serafin Moral, Juan Verdegay-Lopez
Abstract:
In this paper, we consider several types of information and methods of combination associated with incomplete probabilistic systems. We discriminate between 'a priori' and evidential information. The former one is a description of the whole population, the latest is a restriction based on observations for a particular case. Then, we propose different combination methods for each one of them. We also consider conditioning as the heterogeneous combination of 'a priori' and evidential information. The evidential information is represented as a convex set of likelihood functions. These will have an associated possibility distribution with behavior according to classical Possibility Theory.
Keywords:
Pages: 61-68
PS Link:
PDF Link: /papers/91/p61-cano.pdf
BibTex:
@INPROCEEDINGS{Cano91,
AUTHOR = "Jose Cano and Serafin Moral and Juan Verdegay-Lopez",
TITLE = "Combination of Upper and Lower Probabilities",
BOOKTITLE = "Proceedings of the Seventh Conference Annual Conference on Uncertainty in Artificial Intelligence (UAI-91)",
PUBLISHER = "Morgan Kaufmann",
ADDRESS = "San Mateo, CA",
YEAR = "1991",
PAGES = "61--68"
}


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